System and method for monitoring containment of an epidemic

Abstract

A system and method is disclosed for monitoring the containment of an epidemic in relation to a location-based restriction using an anonymized database of spending records. The system measures the effectiveness of a restriction by analyzing the spending records of individuals in the population and identifies transaction trends that relate to the restriction and correlates them to the effectiveness of the restriction. Based on the identified transaction trends, the system calculates the effectiveness and analyzes the restrictions according to expected trends and models of epidemic spread by geography. The system utilizes the measured effectiveness and predictive analysis to generate notifications if the effectiveness does not meet prescribed requirements and to recommend corrective action. In addition, the system can dynamically update restrictions, implement new restrictions and in certain embodiments, the system can elicit (and respond to) actions that are taken at remote devices, such as mobile phones, computers and POS terminals.

Description

TECHNICAL FIELD OF THE DISCLOSURE[0001]This patent application relates generally to the field of monitoring disease outbreaks, and more particularly to detecting and monitoring containment of an epidemic in relation to a location-based restriction using spending records.BACKGROUND OF THE DISCLOSURE[0002]Disease surveillance is a practice by which the spread of disease is monitored in order to predict, observe, and minimize the harm caused by outbreak, epidemic, and pandemic situations. In order to slow down the spread of the disease, location-based restrictions can be implemented that are aimed at limiting the movement of citizens around a geographic location. For instance, restrictions can include forced closures of large and popular public spaces such as airports, universities and market places where people come in contact with each other and the risk of disease transmission is higher.[0003]It is difficult to monitor and understand human mobility and activity during an epidemic. S...

AI Technical Summary

Problems solved by technology

For instance, restrictions can include forced closures of large and popular public spaces such as airports, universities and market places where people come in contact with each other and the risk of disease transmission is higher.

It is difficult to monitor and understand human mobility and activity during an epidemic.

Such efforts commonly require human monitoring, which can be costly.

Moreover, the information gathered from human monitoring is often incomplete and not detailed enough to understand nuances of human mobility and behavior.

However, this high-level and limited sample of information can be incomplete and is ultimately not detailed enough to develop a meaningful understanding of the actual movements and habits of the relevant subsets of individuals in the population in response to the restriction.

This lack of meaningful data makes it difficult to preemptively warn individuals in high risk areas, or take preventative measures such as implementing additional restrictions, especially when the infection is a rapidly spreading through the population.

Thus, it can be appreciated that current methods for disease surveillance present challenges to identifying effective locations for implementing location-based restrictions on mobility and, once a restriction is in place, evaluating how effective the restrictions are at containing the disease spread (e.g., pandemic / epidemic).

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